Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
41–49 of 49 posts
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#42I'm impressed with Cortex - All industry leaders (Google, Siri, Alexa) answer "Who killed John Wilkes Booth" with "Abraham Lincoln," but this gives the correct answer. It shows that it has a deeper understanding of it's data sources.
> What is the most dangerous bear? Winnie - The - Pooh
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#43How is this like, or better than Evi, which has origins in 2007 and is now part of Alexa according to wikipedia? https://en.m.wikipedia.org/wiki/Evi_(software)
We think being able to understand the semantic meaning behind language through our graph of relationships and entities in a sentence are going to be critical in building more robust conversational interfaces. So companies we are talking to now include companies who want to use it for natural language search or messaging apps.
Of course, we think the knowledge graph is useful as well in democratizing the technology since WolframAlpha is absurdly expensive ($25-50 CPM) and the Google KnowledgeGraph API is limited to 100,000 queries a day with no option to pay for more and doesn't handle natural language question answering.
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#44Will the document summarization API summarize and rewrite the content or just a summary of the original content without a rewrite?
Yes, it will perform abstractive summarization (re-writing the language in the text) vs. just extractive summarization, which just pulls out high-importance sentences from text. But we'll offer both just in case.
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#45Very interesting. Needs to account for things like low literacy in certain areas. Medical literacy is a big gap for a lot of people. Asked "What is myocardial infarction? Correct article returned. Asked "What is myocardial infraction?" Got article for Civil infraction. "What is hyperkalemia?" returned a result. "What is high potassium?" No result.
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#46How is this like, or better than Evi, which has origins in 2007 and is now part of Alexa according to wikipedia? https://en.m.wikipedia.org/wiki/Evi_(software)
Good question! We mentioned this in another comment, but a lot of the comments on this thread are about our Cortex Knowledge Graph API, but we actually think of the Sapien Language Engine API as our main product. We think being able to understand the semantic meaning behind language through our graph of relationships and entities in a sentence are going to be critical in building more robust conversational interfaces…
It will be interesting to see how other people apply this without competing with Google, Amazon, or Apple directly.
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#47Earlier quoted context omitted.
Yes, it will perform abstractive summarization (re-writing the language in the text) vs. just extractive summarization, which just pulls out high-importance sentences from text. But we'll offer both just in case.
I have been looking for an abstractive summarization API for quite some time, any idea when you will be releasing this. If you are planning any sort of beta I would love to be part of it :)
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#48Earlier quoted context omitted.
Good question! We mentioned this in another comment, but a lot of the comments on this thread are about our Cortex Knowledge Graph API, but we actually think of the Sapien Language Engine API as our main product. We think being able to understand the semantic meaning behind language through our graph of relationships and entities in a sentence are going to be critical in building more robust conversational interfaces…
Got it. So really, its a piece of what Evi did, but you are making that a service. It will be interesting to see how other people apply this without competing with Google, Amazon, or Apple directly.